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Developing a Web-based tool that involves the input, buy-in, and collaboration of multiple stakeholders and contractors is a complex process. Several elements facilitated the development of the Web-based Diabetes Indicators and Data Sources Internet Tool (DIDIT). The DIDIT is designed to enhance the ability of staff within the state-based Diabetes Prevention and Control Programs (DPCPs) and the Centers for Disease Control and Prevention (CDC) to perform diabetes surveillance. It contains information on 38 diabetes indicators (measures of health or factors associated with health) and 12 national- and state-level data sources. Developing the DIDIT required one contractor to conduct research on content for diabetes indicators and data sources and another contractor to develop the Web-based application to house and manage the information. During 3 years, a work group composed of representatives from the DPCPs and the Division of Diabetes Translation (DDT) at the CDC guided the development process by 1) gathering information on and communicating the needs of users and their vision for the DIDIT, 2) reviewing and approving content, and 3) providing input into the design and system functions. Strong leadership and vision of the project lead, clear communication and collaboration among all team members, and a commitment from the management of the DDT were essential elements in developing and implementing the DIDIT. Expertise in diabetes surveillance and software development, enthusiasm, and dedication were also instrumental in developing the DIDIT.

Diabetes has emerged as a major public health concern in developing nations. Health systems in most developing countries are yet to integrate effective prevention and control programs for diabetes into routine health care services. Given the inadequate human resources and underfunctioning health systems, we need novel and innovative approaches to combat diabetes in developing-country settings. In this regard, the tremendous advances in telecommunication technology, particularly cell phones, can be harnessed to improve diabetes care. Cell phones could serve as a tool for collecting information on surveillance, service delivery, evidence-based care, management, and supply systems pertaining to diabetes from primary care settings in addition to providing health messages as part of diabetes education. As a screening/diagnostic tool for diabetes, cell phones can aid the health workers in undertaking screening and diagnostic and follow-up care for diabetes in the community. Cell phones are also capable of acting as a vehicle for continuing medical education; a decision support system for evidence-based management; and a tool for patient education, self-management, and compliance. However, for widespread use, we need robust evaluations of cell phone applications in existing practices and appropriate interventions in diabetes.

The National Diabetes Education Program, cosponsored by the National Institutes of Health and the Centers for Disease Control and Prevention, employs mass media communications, public-private partnerships, and dissemination of information and education tools to address the diabetes epidemic in the United States. The program's goal is to help reduce the morbidity and mortality from diabetes and its complications by improving the treatment and outcomes for people with diabetes, promoting early diagnosis, and preventing onset of diabetes. Evaluation is an integral component of the National Diabetes Education Program's planning and implementation process. The program's evaluation is based on the Centers for Disease Control and Prevention's Framework for Program Evaluation in Public Health, which has guided program planners and evaluators in developing measurable short-term, midterm, and long-term outcomes. We describe how the National Diabetes Education Program has applied the evaluation framework, demonstrating how multifaceted health communications programs can design program evaluations to answer key questions about program processes and outcomes.

If current trends continue, health systems will soon be overwhelmed by type 2 diabetes mellitus. Successful population-based diabetes prevention and control efforts require a sound and continually improving infrastructure. In states and U.S. territories, the Diabetes Prevention and Control Programs supported by the U.S. Centers for Disease Control and Prevention's Division of Diabetes Translation serve as a fulcrum for building and refining the infrastructure that links diverse and dynamic partners dedicated to increasing the years and quality of life and achieving health equity among people with and at risk for diabetes. The National Public Health Performance Standards offer a conceptual framework that articulates the requisite infrastructure and services provided by an interconnected network of intersectoral partners to strengthen the public health response to diabetes. These standards associated with the Essential Public Health Services are valuable tools to assess the status of the performance of the health system's infrastructure to guide improvement. The process of engaging system partners in a system-wide assessment informs and leverages cross-sectoral assets to improve health outcomes for citizens in communities shouldering the growing burden of diabetes.

Health behaviors are a leading cause of illness and death in the United States. Efforts to improve public health require information on the prevalence of health behaviors in populations — not only to target programs to areas of most need but also to evaluate the effectiveness of intervention efforts. Telephone surveys, such as the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System, are a good way to assess health behaviors in populations. These data provide estimates at the national and state level but often require multiple years of data to provide reliable estimates at the local level. With changes in telephone use (eg, rapid decline in the ownership of landlines), innovative methods to collect data on health behaviors, such as in health care settings or through Internet-based surveys, need to be developed.

Background

There is great concern within health surveillance, on how to grapple with environmental degradation, rapid urbanization, population mobility and growth. The Internet has emerged as an efficient way to share health information, enabling users to access and understand data at their fingertips. Increasingly complex problems in the health field require increasingly sophisticated computer software, distributed computing power, and standardized data sharing. To address this need, Web-based mapping is now emerging as an important tool to enable health practitioners, policy makers, and the public to understand spatial health risks, population health trends and vulnerabilities. Today several web-based health applications generate dynamic maps; however, for people to fully interpret the maps they need data source description and the method used in the data analysis or statistical modeling. For the representation of health information through Web-mapping applications, there still lacks a standard format to accommodate all fixed (such as location) and variable (such as age, gender, health outcome, etc) indicators in the representation of health information. Furthermore, net-centric computing has not been adequately applied to support flexible health data processing and mapping online.

Results

The authors of this study designed a HEalth Representation XML (HERXML) schema that consists of the semantic (e.g., health activity description, the data sources description, the statistical methodology used for analysis), geometric, and cartographical representations of health data. A case study has been carried on the development of web application and services within the Canadian Geospatial Data Infrastructure (CGDI) framework for community health programs of the New Brunswick Lung Association. This study facilitated the online processing, mapping and sharing of health information, with the use of HERXML and Open Geospatial Consortium (OGC) services. It brought a new solution in better health data representation and initial exploration of the Web-based processing of health information.

Conclusion

The designed HERXML has been proven to be an appropriate solution in supporting the Web representation of health information. It can be used by health practitioners, policy makers, and the public in disease etiology, health planning, health resource management, health promotion and health education. The utilization of Web-based processing services in this study provides a flexible way for users to select and use certain processing functions for health data processing and mapping via the Web. This research provides easy access to geospatial and health data in understanding the trends of diseases, and promotes the growth and enrichment of the CGDI in the public health sector.

Introduction

Electronic health record (EHR) data enhance opportunities for conducting surveillance of diabetes. The objective of this study was to identify the number of people with diabetes from a diabetes DataLink developed as part of the SUPREME-DM (SUrveillance, PREvention, and ManagEment of Diabetes Mellitus) project, a consortium of 11 integrated health systems that use comprehensive EHR data for research.

Methods

We identified all members of 11 health care systems who had any enrollment from January 2005 through December 2009. For these members, we searched inpatient and outpatient diagnosis codes, laboratory test results, and pharmaceutical dispensings from January 2000 through December 2009 to create indicator variables that could potentially identify a person with diabetes. Using this information, we estimated the number of people with diabetes and among them, the number of incident cases, defined as indication of diabetes after at least 2 years of continuous health system enrollment.

Results

The 11 health systems contributed 15,765,529 unique members, of whom 1,085,947 (6.9%) met 1 or more study criteria for diabetes. The nonstandardized proportion meeting study criteria for diabetes ranged from 4.2% to 12.4% across sites. Most members with diabetes (88%) met multiple criteria. Of the members with diabetes, 428,349 (39.4%) were incident cases.

Conclusion

The SUPREME-DM DataLink is a unique resource that provides an opportunity to conduct comparative effectiveness research, epidemiologic surveillance including longitudinal analyses, and population-based care management studies of people with diabetes. It also provides a useful data source for pragmatic clinical trials of prevention or treatment interventions.

In January 2001 the Pew Environmental Health Commission called for the creation of a coordinated public health system to prevent disease in the United States by tracking and combating environmental health threats. In response, the Centers for Disease Control and Prevention initiated the Environmental Public Health Tracking (EPHT) Program to integrate three distinct components of hazard monitoring and exposure and health effects surveillance into a cohesive tracking network. Uniform and acceptable data standards, easily understood case definitions, and improved communication between health and environmental agencies are just a few of the challenges that must be addressed for this network to be effective. The nascent EPHT program is attempting to respond to these challenges by drawing on a wide range of expertise from federal agencies, state health and environmental agencies, nongovernmental organizations, and the program’s academic Centers of Excellence. In this mini-monograph, we present innovative strategies and methods that are being applied to the broad scope of important and complex environmental public health problems by developing EPHT programs. The data resulting from this program can be used to identify areas and populations most likely to be affected by environmental contamination and to provide important information on the health and environmental status of communities. EPHT will develop valuable data on possible associations between the environment and the risk of noninfectious health effects. These data can be used to reduce the burden of adverse health effects on the American public.

Background

Type 2 Diabetes Mellitus (T2DM) has become a major public health challenge in India. Factors relevant to the development and implementation of diabetes prevention programmes in resource-constrained countries, such as India, have been under-studied. The purpose of this study is to describe the findings from research aimed at informing the development and evaluation of a Diabetes Prevention Programme in Kerala, India (K-DPP).

Methods

Data were collected from three main sources: (1) a systematic review of key research literature; (2) a review of relevant policy documents; and (3) focus groups conducted among individuals with a high risk of progressing to diabetes. The key findings were then triangulated and synthesised.

Results

Prevalence of risk factors for diabetes is very high and increasing in Kerala. This situation is largely attributable to rapid changes in the lifestyle of people living in this state of India. The findings from the systematic review and focus groups identified many environmental and personal determinants of these unhealthy lifestyle changes, including: less than ideal accessibility to and availability of health services; cultural values and norms; optimistic bias and other misconceptions related to risk; and low expectations regarding one’s ability to make lifestyle changes in order to influence health and disease outcomes. On the other hand, there are existing intervention trials conducted in India which suggests that risk reduction is possible. These programmes utilize multi-level strategies including mass media, as well as strategies to enhance community and individual empowerment. India’s national programme for the prevention and control of major non-communicable diseases (NCD) also provide a supportive environment for further community-based efforts to prevent diabetes.

Conclusion

These findings provide strong support for undertaking more research into the conduct of community-based diabetes prevention in the rural areas of Kerala. We aim to develop, implement and evaluate a group-based peer support programme that will address cultural and family determinants of lifestyle risks, including family decision-making regarding adoption of healthy dietary and physical activity patterns. Furthermore, we believe that this approach will be feasible, acceptable and effective in these communities; with the potential for scale-up in other parts of India.

Free or low-cost unstructured reports offer an alternative to traditional indicator-based outbreak reporting.

Free or low-cost sources of unstructured information, such as Internet news and online discussion sites, provide detailed local and near real-time data on disease outbreaks, even in countries that lack traditional public health surveillance. To improve public health surveillance and, ultimately, interventions, we examined 3 primary systems that process event-based outbreak information: Global Public Health Intelligence Network, HealthMap, and EpiSPIDER. Despite similarities among them, these systems are highly complementary because they monitor different data types, rely on varying levels of automation and human analysis, and distribute distinct information. Future development should focus on linking these systems more closely to public health practitioners in the field and establishing collaborative networks for alert verification and dissemination. Such development would further establish event-based monitoring as an invaluable public health resource that provides critical context and an alternative to traditional indicator-based outbreak reporting.

SYNOPSIS

This article describes the New York State Department of Health's GeoDatabase project, which developed new methods and techniques for designing and building a geocoding and mapping data repository for sexually transmitted disease (STD) control. The GeoDatabase development was supported through the Centers for Disease Control and Prevention's Outcome Assessment through Systems of Integrated Surveillance workgroup. The design and operation of the GeoDatabase relied upon commercial-off-the-shelf tools that other public health programs may also use for disease-control systems. This article provides a blueprint of the structure and software used to build the GeoDatabase and integrate location data from multiple data sources into the everyday activities of STD control programs.

To allow public health officials to uniformly define, collect, and report chronic disease data, Indicators for Chronic Disease Surveillance was released by the Council of State and Territorial Epidemiologists in 1999. This publication provided standard definitions for 73 indicators developed by epidemiologists and chronic disease program directors at the state and federal levels. The indicators were selected because of their importance to public health and the availability of state-level data. This report describes the latest revisions to the chronic disease indicators published in 2004. The revised set of 92 indicators includes 24 for cancer; 15 for cardiovascular disease; 11 for diabetes; 7 for alcohol; 5 each for nutrition and tobacco; 3 each for oral health, physical activity, and renal disease; and 2 each for asthma, osteoporosis, and immunizations. The remaining 10 indicators cover such overarching conditions as poverty, education, and life expectancy. Although multiple states have used the indicators, wider adoption depends on increased epidemiology capacity at the state level and improved access to surveillance data.

Introduction

People with a family history of diabetes are at increased risk of developing diabetes; however, the effect of family history of diabetes on health care provider practice and patient behavior has not been well defined.

Methods

We analyzed data from the 2005 Oregon Behavioral Risk Factor Surveillance System, a state-based, random-digit–dialed telephone survey, to evaluate, among people with diabetes, associations between family history of diabetes and 1) patients' reports of health care provider practices, 2) patients' perceived risk of developing diabetes, and 3) patients' behaviors associated with an increased risk of developing diabetes.

Results

Compared with respondents at average risk, respondents with a positive family history (strong or moderate familial risk for diabetes) were more likely to report that their health care provider collects family history information about diabetes, discusses the risk of developing diabetes or other chronic conditions, and makes recommendations to change their diet or exercise behaviors to reduce the chance of developing diabetes. Respondents with a strong family history of diabetes were 5 times more likely to be very or somewhat worried about developing diabetes than were people at average risk (odds ratio [OR], 5.0; 95% confidence interval [CI], 4.0-6.2). Compared with respondents at average risk, respondents with a strong family history were more likely to report making changes in diet and exercise (OR, 1.7; 95% CI, 1.4-2.1).

Conclusion

Integrating family history of diabetes into clinical practice offers opportunities to improve the effectiveness of diabetes detection and to promote interventions aimed at preventing or delaying the development of diabetes in people at high risk.

Background

Emerging public health threats often originate in resource-limited countries. In recognition of this fact, the World Health Organization issued revised International Health Regulations in 2005, which call for significantly increased reporting and response capabilities for all signatory nations. Electronic biosurveillance systems can improve the timeliness of public health data collection, aid in the early detection of and response to disease outbreaks, and enhance situational awareness.

Methods

As components of its Suite for Automated Global bioSurveillance (SAGES) program, The Johns Hopkins University Applied Physics Laboratory developed two open-source, electronic biosurveillance systems for use in resource-limited settings. OpenESSENCE provides web-based data entry, analysis, and reporting. ESSENCE Desktop Edition provides similar capabilities for settings without internet access. Both systems may be configured to collect data using locally available cell phone technologies.

Results

ESSENCE Desktop Edition has been deployed for two years in the Republic of the Philippines. Local health clinics have rapidly adopted the new technology to provide daily reporting, thus eliminating the two-to-three week data lag of the previous paper-based system.

Conclusions

OpenESSENCE and ESSENCE Desktop Edition are two open-source software products with the capability of significantly improving disease surveillance in a wide range of resource-limited settings. These products, and other emerging surveillance technologies, can assist resource-limited countries compliance with the revised International Health Regulations.

Although public debate in Canada about climate change and air pollution is louder than ever, the state of the environment remains a relatively neglected determinant of health, and environmental public health infrastructure and programs are poorly developed. Health Canada has only recently begun to develop a national environmental public health tracking or surveillance system. The authors review progress on environmental public health tracking in other jurisdictions and suggest a strategic approach to the development of a coherent national system of sensitive, targeted surveillance indicators for environmental health by addressing the following questions: Which environmental hazards and exposures, and which health effects along the continuum from “release” to “health effect,” should be tracked? Which indicators are scientifically robust and practical for tracking environmental health problems in Canada?

Clinical observations will allow early detection of emerging diseases in animal to enhance response time and capabilities.

Predicting emerging diseases is among the most difficult challenges facing researchers and health managers. We present available approaches and tools to detect emerging diseases in animals based on clinical observations of farm animals by veterinarians. Three information systems are described and discussed: Veterinary Practitioner Aided Disease Surveillance in New Zealand, the Rapid Syndrome Validation Project—Animal in the United States, and "émergences" in France. These systems are based on syndromic surveillance with the notification of every case or of specific clinical syndromes or on the notification of atypical clinical cases. Data are entered by field veterinarians into forms available through Internet-accessible devices. Beyond challenges of implementing new information systems, minimizing economic and health effects from emerging diseases in animals requires strong synergies across a group of field partners, in research, and in international animal and public health customs and practices.

Infodemiology can be defined as the science of distribution and determinants of information in an electronic medium, specifically the Internet, or in a population, with the ultimate aim to inform public health and public policy. Infodemiology data can be collected and analyzed in near real time. Examples for infodemiology applications include: the analysis of queries from Internet search engines to predict disease outbreaks (eg. influenza); monitoring peoples' status updates on microblogs such as Twitter for syndromic surveillance; detecting and quantifying disparities in health information availability; identifying and monitoring of public health relevant publications on the Internet (eg. anti-vaccination sites, but also news articles or expert-curated outbreak reports); automated tools to measure information diffusion and knowledge translation, and tracking the effectiveness of health marketing campaigns. Moreover, analyzing how people search and navigate the Internet for health-related information, as well as how they communicate and share this information, can provide valuable insights into health-related behavior of populations. Seven years after the infodemiology concept was first introduced, this paper revisits the emerging fields of infodemiology and infoveillance and proposes an expanded framework, introducing some basic metrics such as information prevalence, concept occurrence ratios, and information incidence. The framework distinguishes supply-based applications (analyzing what is being published on the Internet, eg. on Web sites, newsgroups, blogs, microblogs and social media) from demand-based methods (search and navigation behavior), and further distinguishes passive from active infoveillance methods. Infodemiology metrics follow population health relevant events or predict them. Thus, these metrics and methods are potentially useful for public health practice and research, and should be further developed and standardized.

The Tanzania Field Epidemiology and Laboratory Training Program (TFELTP) was established in 2008 as a partnership among the Ministry of Health and Social Welfare (MOHSW), Muhimbili University of Health and Allied Sciences, National Institute for Medical Research, and local and international partners. TFELTP was established to strengthen the capacity of MOHSW to conduct public health surveillance and response, manage national disease control and prevention programs, and to enhance public health laboratory support for surveillance, diagnosis, treatment and disease monitoring. TFELTP is a 2-year full-time training program with approximately 25% time spent in class, and 75% in the field. TFELTP offers two tracks leading to an MSc degree in either Applied Epidemiology or, Epidemiology and Laboratory Management. Since 2008, the program has enrolled a total of 33 trainees (23 males, 10 females). Of these, 11 were enrolled in 2008 and 100% graduated in 2010. All 11 graduates of cohort 1 are currently employed in public health positions within the country. Demand for the program as measured by the number of applicants has grown from 28 in 2008 to 56 in 2011. While training the public health leaders of the country, TFELTP has also provided essential service to the country in responding to high-profile disease outbreaks, and evaluating and improving its public health surveillance systems and diseases control programs. TFELTP was involved in the country assessment of the revised International Health Regulations (IHR) core capabilities, development of the Tanzania IHR plan, and incorporation of IHR into the revised Tanzania Integrated Disease Surveillance and Response (IDSR) guidelines. TFELTP is training a competent core group of public health leaders for Tanzania, as well as providing much needed service to the MOHSW in the areas of routine surveillance, outbreak detection and response, and disease program management. However, the immediate challenges that the program must address include development of a full range of in-country teaching capacity for the program, as well as a career path for graduates.

Background

According to 2003 Behavioral Risk Factor Surveillance System data, South Carolina has the fourth highest rate of overall diabetes among the 50 states (9.3%) but the second highest rate among African Americans (15.5%). Nationwide, African Americans are disproportionately affected by diabetes. In addition, 40% of the African American population in South Carolina lives in a rural area, and approximately 26% live at or below the poverty level. Lack of access to health care and diabetes education are additional barriers for people with diabetes and their families.

Context

Since 1997, the South Carolina Diabetes Prevention and Control Program and the Diabetes Today Advisory Council have sponsored the African American Conference on Diabetes, which targets African Americans with diabetes, their families, and their caregivers. This article describes the evolution of the conference and its evaluation.

Methods

In 2002, we conducted focus groups with 20 African American conference attendees with diabetes to 1) assess the program's effects, 2) determine how to reach more individuals, and 3) improve programming. In 2004, we incorporated the preconference and postconference Diabetes Understanding Scale survey to assess the cognitive impact of the conference on participants.

Consequences

Focus group results revealed that participants wanted to attend the conference because of the opportunity to increase their knowledge and change their behaviors through 1) education, 2) social support, 3) resources, and 4) logistics. Self-rated understanding increased significantly after the conference for each cognitive understanding item on the Diabetes Understanding Scale.

Interpretation

Focus group results suggested that participants who continue to attend the conference year after year may improve diabetes self-management skills. A quantitative evaluation showed that this 1-day diabetes education conference significantly increased short-term, self-rated cognitive understanding of diabetes behaviors.

During the last 2 decades of the 20th century, few national, state, or local oral health programs were able to conduct public health surveillance in a timely fashion. Under the leadership of the Association of State and Territorial Dental Directors and with substantial support from the Division of Oral Health at the Centers for Disease Control and Prevention, the National Oral Health Surveillance System was established as a first step in helping oral health programs routinely document population needs and program impact with standard, feasible methods. In 1999, the Council of State and Territorial Epidemiologists approved 7 oral health indicators for public health surveillance: 3 for adults (most recent dental visit, most recent dental cleaning, total tooth loss) using data from the Behavioral Risk Factor Surveillance System; 3 for third-grade students (presence of treated or untreated dental caries, untreated tooth decay, dental sealants) collected by states using a standard screening protocol; and the percentage of the population served by public water systems that receives optimally fluoridated water, tracked through the Water Fluoridation Reporting System. The Web site that describes the National Oral Health Surveillance System (http://www.cdc.gov/nohss/) and provides access to current indicators was launched in 2001 with adult and water fluoridation data for all states; child indicators were added later. Data are now available electronically for 35 to 51 states (including the District of Columbia), depending on the indicator, indicating progress toward state-specific monitoring of these oral health indicators.

The Centers for Disease Control and Prevention in the U.S. Department of Health and Human Services is working with selected state and local health departments, academic centers, and others to develop an environmental public health tracking initiative to improve geographic and temporal surveillance of environmental hazards, exposures, and related health outcomes. The objective is to support policy strategies and interventions for disease prevention by communities and environmental health agencies at the federal, state, and local levels. The first 3 years of the initiative focused on supporting states and cities in developing capacity, information technology infrastructure, and pilot projects to demonstrate electronic linkage of environmental hazard or exposure data and disease data. The next phase requires implementation across states. This transition could provide opportunities to further integrate research, surveillance, and practice through attention to four areas. The first is to develop a shared and transparent knowledge base that draws on environmental health research and substantiates decisions about what to track and the interpretation of results. The second is to identify and address information needs of policy and stakeholder audiences in environmental health. The third is to adopt mechanisms for coordination, decision making, and governance that can incorporate and support the major entities involved. The fourth is to promote disease prevention by systematically identifying and addressing population-level environmental determinants of health and disease.

The Steps to a HealthierUS Cooperative Agreement Program (Steps Program) enables funded communities to implement chronic disease prevention and health promotion efforts to reduce the burden of diabetes, obesity, asthma, and related risk factors. At both the national and community levels, investment in surveillance and program evaluation is substantial. Public health practitioners engaged in program evaluation planning often identify desired outcomes, related indicators, and data collection methods but may pay only limited attention to an overarching vision for program evaluation among participating sites.

We developed a set of foundational elements to provide a vision of program evaluation that informs the technical decisions made throughout the evaluation process. Given the diversity of activities across the Steps Program and the need for coordination between national- and community-level evaluation efforts, our recommendations to guide program evaluation practice are explicit yet leave room for site-specific context and needs. Staff across the Steps Program must consider these foundational elements to prepare a formal plan for program evaluation. Attention to each element moves the Steps Program closer to well-designed and complementary plans for program evaluation at the national, state, and community levels.

In public health research and practice, quality of life is increasingly acknowledged as a valid and appropriate indicator of service need and intervention outcomes. Health-related quality of life measures, including objective and subjective assessments of health, are particularly useful for evaluating efforts in the prevention of disabling chronic diseases. Such data can inform health policy, planning, and practice. Mechanisms for routinely monitoring quality of life of populations at the State and local levels are currently lacking, however. This article discusses the rationale for and concepts measured by four quality of life questions developed for the 1993 Behavioral Risk Factor Surveillance System, a State-based telephone surveillance system. To encourage quality of life surveillance by States, the Centers for Disease Control and Prevention's National Center for Chronic Disease Prevention and Health Promotion held two related workshops, one in December 1991 and the other in June 1992. The workshops convened experts in quality of life and functional status measurement and resulted in the formulation of items for the Behavioral Risk Factor Surveillance System on self-perceived health, recent physical and mental health, and recent limitation in usual activities. The criteria, including feasibility and generalizability, considered by the Centers for Disease Control and Prevention and the workshop participants in the selection and development of these items are discussed. A model that conceptualizes the relationship of quality of life domains measured by the four survey items is presented and validated with preliminary data from the 1993 Behavioral Risk Factor Surveillance System. Finally, how States can use these measures to track progress towards the Year 2000 goal of improving quality of life is discussed.

This article synthesizes and extends discussions held during an international meeting on “Surveillance for Decision Making: The Example of 2009 Pandemic Influenza A/H1N1,” held at the Center for Communicable Disease Dynamics (CCDD), Harvard School of Public Health, on June 14 and 15, 2010. The meeting involved local, national, and global health authorities and academics representing 7 countries on 4 continents. We define the needs for surveillance in terms of the key decisions that must be made in response to a pandemic: how large a response to mount and which control measures to implement, for whom, and when. In doing so, we specify the quantitative evidence required to make informed decisions. We then describe the sources of surveillance and other population-based data that can presently—or in the future—form the basis for such evidence, and the interpretive tools needed to process raw surveillance data. We describe other inputs to decision making besides epidemiologic and surveillance data, and we conclude with key lessons of the 2009 pandemic for designing and planning surveillance in the future.

This article synthesizes discussions held during an international meeting, “Surveillance for Decision Making: The Example of 2009 Pandemic Influenza A/H1N1,” held at Harvard School of Public Health in June 2010. It defines the needs for surveillance in terms of the key decisions that must be made in response to a pandemic: how large a response to mount and which control measures to implement, for whom, and when. The article describes the sources of surveillance and other population-based data that can form the basis for such evidence, and the interpretive tools needed to process raw surveillance data. It concludes with key lessons of the 2009 pandemic for designing and planning surveillance in the future.

HepSEQ is a repository for an extensive library of public health and molecular data relating to hepatitis B virus (HBV) infection collected from international sources. It is hosted by the Centre for Infections, Health Protection Agency (HPA), England, United Kingdom. This repository has been developed as a web-enabled, quality-controlled database to act as a tool for surveillance, HBV case management and for research. The web front-end for the database system can be accessed from . The format of the database system allows for comprehensive molecular, clinical and epidemiological data to be deposited into a functional database, to search and manipulate the stored data and to extract and visualize the information on epidemiological, virological, clinical, nucleotide sequence and mutational aspects of HBV infection through web front-end. Specific tools, built into the database, can be utilized to analyse deposited data and provide information on HBV genotype, identify mutations with known clinical significance (e.g. vaccine escape, precore and antiviral-resistant mutations) and carry out sequence homology searches against other deposited strains. Further mechanisms are also in place to allow specific tailored searches of the database to be undertaken.